Assessing Carbon Footprint and Inter-Regional Carbon Transfer in China Based on a Multi-Regional Input-Output Model

China has been the largest carbon emitter in the world since 2007 and is thus confronted with huge emission reduction pressures. The regional differences in socio-economic development lead to complex inter-provincial carbon transfer in China, which hinders the determination of the emission reduction responsibilities for the various provinces. Based on the latest multi-regional input-output data, this study analyzes the carbon footprint, inter-provincial carbon transfer, and the corresponding variations of 30 provinces in China from 2007 to 2010. The results show that the domestic carbon footprint increased from 4578 Mt in 2007 to 6252 Mt in 2010. Provinces with high carbon footprints were mainly found in central China, such as Shandong, Jiangsu, and Henan. Carbon footprints of the developed coastal provinces were greater than those of less developed provinces in Northwestern China. Per capita GDP (Gross Domestic Product) was positively correlated to the per capita carbon footprint, indicating a positive relationship between the economic development level and corresponding carbon emissions. Provincial carbon inflows were found to have increased steadily (ranging between 32% and 41%) from 2007 to 2010. The increases in direct carbon emissions varied largely among different provinces, ranging from below 30% in the developed provinces to more than 60% in the moderately developed provinces (e.g., Sichuan and Chongqing). The embodied carbon transferred from moderately developed or remote provinces to those developed ones. In other words, the carbon emission pressures of the developed provinces were shifted to the less developed provinces. The major paths of carbon flow include the transfers from Hebei to Jiangsu (32.07 Mt), Hebei to Beijing (26.78 Mt), Hebei to Zhejiang (25.60 Mt), and Liaoning to Jilin (27.60 Mt).

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A Dynamic Benchmark System for Per Capita Carbon Emissions in Low-Carbon Counties of China

Energies ◽

10.3390/en14030599 ◽

2021 ◽

Vol 14 (3) ◽

pp. 599

Author(s):

Lijie Gao ◽

Xiaoqi Shang ◽

Fengmei Yang ◽

Longyu Shi

Keyword(s):

Economic Development ◽

Carbon Emissions ◽

Emission Reduction ◽

Best Practice ◽

Indicator System ◽

Kuznets Curve ◽

Low Carbon ◽

Development Stages ◽

Benchmark System ◽

Per Capita

As the most basic unit of the national economy and administrative management, the low-carbon transformation of the vast counties is of great significance to China’s overall greenhouse gas emission reduction. Although the low-carbon evaluation (LCE) indicator system and benchmarks have been extensively studied, most benchmarks ignore the needs of the evaluated object at the development stage. When the local economy develops to a certain level, it may be restricted by static low-carbon target constraints. This study reviews the relevant research on LCE indicator system and benchmarks based on convergence. The Environmental Kuznets Curve (EKC), a dynamic benchmark system for per capita carbon emissions (PCCEs), is proposed for low-carbon counties. Taking Changxing County, Zhejiang Province, China as an example, a dynamic benchmark for PCCEs was established by benchmarking the Carbon Kuznets Curve (CKC) of best practices. Based on the principles of best practice, comparability, data completeness, and the CKC hypothesis acceptance, the best practice database is screened, and Singapore is selected as a potential benchmark. By constructing an econometric model to conduct an empirical study on Singapore’s CKC hypothesis, the regression results of the least squares method support the CKC hypothesis and its rationality as a benchmark. The result of the PCCE benchmarks of Changxing County show that when the per capita income of Changxing County in 2025, 2030, and 2035 reaches USD 19,172.92, USD 24,483.01, and USD 29,366.11, respectively, the corresponding benchmarks should be 14.95 tons CO2/person, 14.70 tons CO2/person, and 13.55 tons CO2/person. For every 1% increase in the county’s per capita income, the PCCE allowable room for growth is 17.6453%. The turning point is when the per capita gross domestic product (PCGDP) is USD 20,843.23 and the PCCE is 15.03 tons of CO2/person, which will occur between 2025 and 2030. Prior to this, the PCCE benchmark increases with the increase of PCGDP. After that, the PCCE benchmark decreases with the increase of PCGDP. The system is economically sensitive, adaptable to different development stages, and enriches the methodology of low-carbon indicator evaluation and benchmark setting at the county scale. It can provide scientific basis for Chinese county decision makers to formulate reasonable targets under the management idea driven by evaluation indicators and emission reduction targets and help counties explore the coordinated paths of economic development and emission reduction in different development stages. It has certain reference significance for other developing regions facing similar challenges of economic development and low-carbon transformation to Changxing County to formulate scientific and reasonable low-carbon emission reduction targets.

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Study on Conduction Paths of Carbon Footprint of Energy Sources Industry among Industries in Henan Province

Advanced Materials Research ◽

10.4028/www.scientific.net/amr.616-618.1185 ◽

2012 ◽

Vol 616-618 ◽

pp. 1185-1189

Author(s):

Qing Xin Liu

Keyword(s):

Carbon Footprint ◽

Carbon Emissions ◽

Emission Reduction ◽

Henan Province ◽

Energy Industry ◽

Energy Sources ◽

Input Output ◽

Conduction Path ◽

Output Coefficient ◽

The Impact

According to Input-Output table portraying the conduction path of carbon footprint among industries, and define the impact of the energy sources industry for other industries on carbon emissions, the paper provide specific and workable methods for energy saving and emission reduction. Constructing the input-output model of carbon footprint of Henan Province by Input-Output method based on the energy consumption data. Using input coefficient, output coefficient and the method of triangulation, identify conduction path of carbon footprint of the energy sources industry among industries in Henan Province. According to the analysis of energy industry in Henan province, the paper introduces the characteristic of carbon emissions of the energy industry and Put forward the ideas of energy conservation and emission reduction taking the energy industry as the breakthrough point.

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The Spatiotemporal Evolution Pattern and Influential Factor of Regional Carbon Emission Convergence in China

Advances in Meteorology ◽

10.1155/2020/4361570 ◽

2020 ◽

Vol 2020 ◽

pp. 1-10 ◽

Cited By ~ 1

Author(s):

Xin Tong

Keyword(s):

Economic Development ◽

Carbon Emissions ◽

Emission Reduction ◽

Carbon Emission ◽

Influential Factor ◽

Spatiotemporal Evolution ◽

Reduction Strategy ◽

Emission Level ◽

Evolution Pattern ◽

Convergence Model

As economic development rapidly progresses in China, a method of carbon emission control that provides reasonable solutions is needed. This paper analyzes the convergence of carbon emission evolutionary characteristics in different regions of China and studies the dynamics of carbon emissions in China based on a convergence model. It was found that the carbon emission levels of each region are prominent in terms of time, and the regional carbon emission level has absolute β characteristics. The regional carbon emission condition β convergences have different convergence paths. Therefore, it is necessary to justify carbon emission reduction in China and put forward an emission reduction strategy.

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Inter-Regional Spillover of Carbon Emissions and Employment in China: Is It Positive or Negative?

Sustainability ◽

10.3390/su11133622 ◽

2019 ◽

Vol 11 (13) ◽

pp. 3622 ◽

Cited By ~ 3

Author(s):

Wenbin Shao ◽

Fangyi Li ◽

Zhaoyang Ye ◽

Zhipeng Tang ◽

Wu Xie ◽

...

Keyword(s):

Economic Development ◽

Carbon Emissions ◽

Decomposition Method ◽

Carbon Emission ◽

Spillover Effects ◽

Efficiency Improvement ◽

Input Output ◽

Coastal Regions ◽

Regional Trade ◽

Positive Spillover

International and inter-regional trade in China has been promoted, the economic and environmental impacts of which are significant in regional development. In this paper, we analyzed the evolution of inter-regional spillover of carbon emissions and employment in China from 2007 to 2012 with structural decomposition method and multi-regional input-output tables. The index of carbon emission per employee (ICE) is designed and compared to indicate positive or negative spillover effects. We find that carbon emissions grow much more rapidly in interior regions than in coastal regions, due to spillover effects and own influences. Spillover effects rarely reduce the ICE of destination regions, but the own influences can decrease it in most regions. Although spillover may contribute to economic development in most regions, it is hardly a driver of efficiency improvement in destination regions. Based on these empirical findings, we put forward specific suggestions to improve the positive spillover effects on different kinds of regions.

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Carbon Footprint Analysis of Bamboo Scrimber Flooring—Implications for Carbon Sequestration of Bamboo Forests and Its Products

Forests ◽

10.3390/f10010051 ◽

2019 ◽

Vol 10 (1) ◽

pp. 51 ◽

Cited By ~ 7

Author(s):

Lei Gu ◽

Yufeng Zhou ◽

Tingting Mei ◽

Guomo Zhou ◽

Lin Xu

Keyword(s):

Carbon Sequestration ◽

Carbon Cycling ◽

Carbon Footprint ◽

Carbon Emissions ◽

Carbon Emission ◽

Carbon Stocks ◽

Bamboo Forest ◽

Carbon Footprints ◽

Production Processes ◽

Bamboo Scrimber

Bamboo forest is characterized by large carbon sequestration capability and it plays an important role in mitigating climate change and global carbon cycling. Previous studies have mostly focused on carbon cycling and carbon stocks in bamboo forest ecosystems, whereas the carbon footprints of bamboo products have not received attention. China is the largest exporting country of bamboo flooring in the world. Estimating the carbon footprint of bamboo flooring is of essential importance for the involved enterprises and consumers to evaluate their own carbon footprints. In this study, we investigated the production processes of bamboo scrimber flooring for outdoor use, a typical bamboo flooring in China. Based on business-to-business (B2B) evaluation method, we assessed CO2 emission and carbon transfer ratio in each step of the production process, including transporting bamboo culms and producing and packing the products. We found that to produce 1 m3 of bamboo scrimber flooring, direct carbon emissions from fossil fuels during transporting raw materials/semi-finished products, from power consumptions during production, and indirect emissions from applying additives were 30.94 kg CO2 eq, 143.37 kg CO2 eq, and 78.34 kg CO2 eq, respectively. After subtracting the 267.54 kg CO2 eq carbon stocks in the product from the 252.65 kg CO2 eq carbon emissions derived within the defined boundary, we found that the carbon footprint of 1 m3 bamboo scrimber flooring was −14.89 kg CO2 eq. Our results indicated that the bamboo scrimber flooring is a negative carbon-emission product. Finally, we discussed factors that influence the carbon footprint of the bamboo flooring and gave suggestions on carbon emission reduction during production processes. This study provided a scientific basis for estimating carbon stocks and carbon footprints of bamboo products and further expanded knowledge on carbon cycling and lifespan of carbon in the bamboo forest ecosystem.

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Accounting for carbon emissions associated with tourism-related consumption

Tourism Economics ◽

10.1177/1354816618754691 ◽

2018 ◽

Vol 24 (5) ◽

pp. 510-525 ◽

Cited By ~ 7

Author(s):

Meiwei Tang ◽

Shouzhong Ge

Keyword(s):

Carbon Dioxide ◽

Gross Domestic Product ◽

Carbon Footprint ◽

Carbon Emissions ◽

Value Added ◽

Total Carbon ◽

Low Carbon ◽

Input Output ◽

Output Table ◽

Goods And Services

This article explores the issues of carbon dioxide (CO2) emissions resulting from the production of the goods and services provided to supply tourism consumption. First, we define the scope of tourism activities and the resulting tourism consumption and tourism direct gross value added (TDGVA). Second, we calculate CO2 emissions for sectors and compile a carbon input-output table (CIOT). Third, we adjust the tourism-related products consumed according to the range of the corresponding sectors of the CIOT. Finally, we use Shanghai as an example to calculate the carbon emissions that result from tourism consumption using the input-output model. This study shows that the TDGVA accounted for 7.97% of the Gross Domestic Product (GDP) in 2012, whereas the carbon footprint of tourism accounted for 20.45% of total carbon emissions. The results demonstrate that tourism is not a low-carbon industry in Shanghai.

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Price Variance in Hybrid-LCA Leads to Significant Uncertainty in Carbon Footprints

Frontiers in Sustainability ◽

10.3389/frsus.2021.666209 ◽

2021 ◽

Vol 2 ◽

Author(s):

Arthur Jakobs ◽

Simon Schulte ◽

Stefan Pauliuk

Keyword(s):

Life Cycle ◽

Carbon Footprint ◽

Commodity Prices ◽

Commodity Price ◽

Double Counting ◽

Input Output ◽

Hybrid Lca ◽

Carbon Footprints ◽

Process Database ◽

Added Uncertainty

Hybrid Life Cycle Assessment (HLCA) methods attempt to address the limitations regarding process coverage and resolution of the more traditional Process- and Input-Output Life Cycle Assessments (PLCA, IOLCA). Due to the use of different units, HLCA methods rely on commodity price information to convert the physical units used in process inventories to the monetary units commonly used in Input-Output models. However, prices for the same commodity can vary significantly between different supply chains, or even between various levels in the same supply chain. The resulting commodity price variance in turn leads to added uncertainty in the hybrid environmental footprint. In this paper we take international trading statistics from BACI/UN-COMTRADE to estimate the variance of commodity prices, and use these in an integrated HLCA model of the process database ecoinvent with the EE-MRIO database EXIOBASE. We show that geographical aggregation of PLCA processes is a significant driver in the price variance of their reference products. We analyse the effect of price variance on process carbon footprint intensities (CFIs) and find that the CFIs of hybridised processes show a median increase of 6–17% due to hybridisation, for two different double counting scenarios, and a median uncertainty of −2 to +4% due to price variance. Furthermore, we illustrate the effect of price variance on the carbon footprint uncertainty in a HLCA study of Swiss household consumption. Although the relative footprint increase due to hybridisation is small to moderate with 8–14% for two different double counting correction strategies, the uncertainty due to price variability of this contribution to the footprint is very high, with 95% confidence intervals of (−28, +90%) and (−23, +68%) relative to the median. The magnitude and high positive skewness of the uncertainty highlights the importance of taking price variance into account when performing hybrid LCA.

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Can CO2 Emission Reduction and Economic Growth Be Compatible? Evidence From China

Frontiers in Energy Research ◽

10.3389/fenrg.2021.693767 ◽

2021 ◽

Vol 9 ◽

Author(s):

Zhuang Zhang ◽

You-Hua Chen ◽

Chien-Ming Wang

Keyword(s):

Economic Growth ◽

Economic Development ◽

Emission Reduction ◽

Co2 Emission ◽

Low Carbon ◽

Co2 Emission Reduction ◽

Low Emission ◽

Aggregate Effects ◽

Per Capita ◽

Low Carbon Energy

The influence of low-carbon energy on economic development is a vital issue. Using the provincial panel data in China from 2000 to 2017, this work investigated the aggregate effects of low-emission electricity. The results showed that 1) when the ratio of low-emission electricity to total electricity increases by 1%, the GDP per capita will increase by 0.16% and CO2 emissions will decrease by 0.848%. In other words, low-emission electricity can achieve the goal of low-carbon economic development; 2) the self-supply of low-emission electricity, rather than trade and efficiency, is the main reason for China’s boosted economic growth; and 3) low-emission electricity increases the regional economic gap in China. The effects of pollution inhibition and economic promotion on low-emission electricity in developed areas are significantly greater than those in less developed areas. Thus, the low-emission electricity policy in China should benefit the economy and avoid the excessive economic gap among regions. Policymakers should vigorously promote the low-emission electricity revolution and pay attention to the inclination of energy policy to the central and western regions.

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Decomposition Analysis of Carbon Emissions from Energy Consumption in Beijing-Tianjin-Hebei, China: A Weighted-Combination Model Based on Logarithmic Mean Divisia Index and Shapley Value

Sustainability ◽

10.3390/su10072535 ◽

2018 ◽

Vol 10 (7) ◽

pp. 2535 ◽

Cited By ~ 6

Author(s):

Yi Liang ◽

Dongxiao Niu ◽

Weiwei Zhou ◽

Yingying Fan

Keyword(s):

Economic Development ◽

Energy Consumption ◽

Carbon Emissions ◽

Emission Reduction ◽

Carbon Emission ◽

Industrial Structure ◽

Logarithmic Mean ◽

Consumption Structure ◽

Consumption Intensity ◽

Weighted Combination

The Beijing-Tianjin-Hebei (B-T-H) region, who captures the national strategic highland in China, has drawn a great deal of attention due to the fog and haze condition and other environmental problems. Further, the high carbon emissions generated by energy consumption has restricted its further coordinated development seriously. In order to accurately analyze the potential influencing factors that contribute to the growth of energy consumption carbon emissions in the B-T-H region, this paper uses the carbon emission coefficient method to measure the carbon emissions of energy consumption in the B-T-H region, using a weighted combination based on Logarithmic Mean Divisia Index (LMDI) and Shapley Value (SV). The effects affecting carbon emissions during 2001–2013 caused from five aspects, including energy consumption structure, energy consumption intensity, industrial structure, economic development and population size, are quantitatively analyzed. The results indicated that: (1) The carbon emissions had shown a sustained growth trend in the B-T-H region on the whole, while the growth rates varied in the three areas. In detail, Hebei Province got the first place in carbon emissions growth, followed by Tianjin and Beijing; (2) economic development was the main driving force for the carbon emissions growth of energy consumption in B-T-H region. Energy consumption structure, population size and industrial structure promoted carbon emissions growth as well, but their effects weakened in turn and were less obvious than that of economic development; (3) energy consumption intensity had played a significant inhibitory role on the carbon emissions growth; (4) it was of great significance to ease the carbon emission-reduction pressure of the B-T-H region from the four aspects of upgrading industrial structure adjustment, making technological progress, optimizing the energy structure and building long-term carbon-emission-reduction mechanisms, so as to promote the coordinated low-carbon development.

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